{"title":"使用智能代理测量用户隐私回报","authors":"A. Yassine, S. Shirmohammadi","doi":"10.1109/CIMSA.2009.5069940","DOIUrl":null,"url":null,"abstract":"As many people are now taking advantages of on-line services, the value of the private data they own comes into sight as a problem of fundamental concern. This paper takes the position that, individuals are entitled to secure control over their personal information, disclosing it as part of a transaction only when they are fairly compensated. To make this a concrete possibility, users require technical instruments to be able to measure their privacy payoff and track the use of their private data. In this paper, we propose an intelligent agent-based framework for privacy payoff measurements and negotiation. Intelligent agents in our system collaboratively work on behalf of users for the goal of maximizing their benefit and protect the use of their private data. The overall framework is described, and a particular simulation experiment is presented to evaluate our approach.","PeriodicalId":178669,"journal":{"name":"2009 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications","volume":"936 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Measuring users' privacy payoff using intelligent agents\",\"authors\":\"A. Yassine, S. Shirmohammadi\",\"doi\":\"10.1109/CIMSA.2009.5069940\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As many people are now taking advantages of on-line services, the value of the private data they own comes into sight as a problem of fundamental concern. This paper takes the position that, individuals are entitled to secure control over their personal information, disclosing it as part of a transaction only when they are fairly compensated. To make this a concrete possibility, users require technical instruments to be able to measure their privacy payoff and track the use of their private data. In this paper, we propose an intelligent agent-based framework for privacy payoff measurements and negotiation. Intelligent agents in our system collaboratively work on behalf of users for the goal of maximizing their benefit and protect the use of their private data. The overall framework is described, and a particular simulation experiment is presented to evaluate our approach.\",\"PeriodicalId\":178669,\"journal\":{\"name\":\"2009 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications\",\"volume\":\"936 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIMSA.2009.5069940\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIMSA.2009.5069940","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Measuring users' privacy payoff using intelligent agents
As many people are now taking advantages of on-line services, the value of the private data they own comes into sight as a problem of fundamental concern. This paper takes the position that, individuals are entitled to secure control over their personal information, disclosing it as part of a transaction only when they are fairly compensated. To make this a concrete possibility, users require technical instruments to be able to measure their privacy payoff and track the use of their private data. In this paper, we propose an intelligent agent-based framework for privacy payoff measurements and negotiation. Intelligent agents in our system collaboratively work on behalf of users for the goal of maximizing their benefit and protect the use of their private data. The overall framework is described, and a particular simulation experiment is presented to evaluate our approach.